Method and system for quantitative determination of software ease of use

ABSTRACT

The present invention uses biometrics for the quantitative determination of software ease of use by collecting biometric data from a software user, identifying changes in the biometric data as the user uses the software, determining if the changes are indicative of software ease of use issues, and generating a signal as output if the changes are determined to be indicative of software ease of use issues. The sensors may be integrated into a computer mouse or other peripheral device with which the user comes in regular contact during use.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of application Ser. No. 11/327,068filed Jan. 6, 2006, now abandoned.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to the field of measuring software ease ofuse.

2. Background Description

Most software systems and applications provide at least one userinterface. Such an interface may be graphical or it may be provided by atext input from a terminal, or from a set of dedicated peripheraldevices. Similarly most applications, middleware and solutions provideuser interfaces for purposes of configuring and installation. A userinterface is required every time a person is expected to be the user ofa software system or application.

It is always desirable, for efficiency purposes, to make interfaces asuser-friendly as possible. The existing art, however, does not provideadequate quantitative methods to measure either ease of use orhuman-friendliness of a user interface in a manner that provides asufficient correlation to the experience of a human being inconfiguring, installing and using the software.

Because ease of use is largely a matter of a user's subjective state ofmind, which may not be susceptible to direct measurement, quantificationof ease of use has relied on developing cognitive complexity metricsthat are based on measurements of user interface actions, such as mouseclicks or other user interventions necessary to complete a process,which are more susceptible than a user's subjective state of mind todirect measurement and quantification. The number of mouse clicksrequired to accomplish a step, or the number of steps required tocomplete a process are only an approximate heuristic. Two clicks can beeasier than one click if it is difficult to find the appropriate placeto click in an one-click interface. For example, one click from apull-down menu of very large items is not necessarily more user-friendlythan two clicks from a set of appropriately-nested and well-presentedpull-down menus arranged to provide information to a user withoutsignificant searching or scrolling. Similarly, two interfaces, bothrequiring a single click, may differ in ease of use if they imposedifferent requirements on a user who is required to scroll or searchthrough information in order to find the appropriate place to click.Since there is no way to understand the actual effect on the humanbeings, these metrics fall short of a satisfactory measure. Somemeasures of ease of configuration count the number of user stepsrequired to configure a software application. However, these suffer fromcomparable limitations, in that a single step that is time-consuming toperform can be more frustrating to users than two or three steps, eachof which takes a relatively small amount of time to perform.

Thus, the existing art does not provide an adequate quantitativedetermination of software ease of use.

SUMMARY OF THE INVENTION

It is therefore the object of the present invention to provide a methodand apparatus for quantitative measure of the ease of use of a userinterface, or of a configuration, installation or usage process, whichmay be directly correlated to the experience that a user may have wheninvoking the specified user interface or going through the specifiedconfiguration process. To this end, the present invention provides amethod, a system, and computer-readable medium providing instruction forusing biometric feedback data to determine software ease of use.

Biometric characteristics have the advantage of being subject to directmeasurement and quantification, which is not true of a user's subjectivestate of mind. Use of biometric data to assess software ease of use canbe deployed in experiments or tests to measure ease of use. Ease of usedata for programs in actual operation can be collected experimentally bymeasuring a user's biometric characteristics, and changes in biometriccharacteristics, as the user performs tasks associated with the softwareconfiguration, installation and usage.

Examples of favorable variations in biometric characteristics mayinclude, but are not limited to, a decrease in the pulse rate or adecrease in blood pressure. Examples of unfavorable variations inbiometric characteristics may include, but are not limited to, anincrease in pulse rate above normal or an increase in blood pressure.

Such biometric characteristics may include, without limitation, a humanbeing's physiological state such as, body temperature, blood pressure,blood oxygen level, heart rate, skin conductance response,electromyographic (EMG) signals, electroencephalographic (EEG) signals,eye saccades or other metabolic processes. Changes in such biometriccharacteristics may be monitored, and a function combining variations indifferent biometric characteristics may be used, to determine the changein the mood of a user. Software would be considered easy to use if itproduces relatively few variations in biometric characteristics, or ifit produces biometric responses experimentally or experientiallydetermined to be positive indicators for ease of use. By contrast,software would be considered difficult to use if, during ease of usetesting, it produces a significant number of biometric responsesexperimentally or experientially determined to be negative indicatorsfor ease of use.

Thus, appropriate biometric measurements can be used to determine iftest users experience problems. Similar biometric measurements, if takenby a device integrated into a personal computer peripheral such as akeyboard or mouse, could be used to identify when a user is experiencingproblems with software and recommend appropriate action such asdirecting a user to call a help-desk, displaying links to self-servehelp pages on the web, or other appropriate action.

In order to determine the software complexity of the configuration,installation or usage process, the biometrics characteristics of theuser are measured at least twice, at the beginning of the process and atthe end of the process. The user's response to the experience of usingthe software can be observed through differences in these measurements.Software ease-of-use can then be determined through changes in thebiometric characteristics at the beginning and the end of the process.

It is quite common for users of a software application to switch betweenseveral applications during its use. As an example, the use of anorder-entry system may also be switching to browsing another web-browserduring the invocation of the program. By correlating the applicationthat a user is currently engaged in with the biometric measurementsobtained from the devices, software ease of use can be done whilefiltering out the interactions of the user with other applications thatmay be concurrently running on the computer system.

One quantitative measure of software complexity can be obtained bycomputing a weighted average of the changes in the variouscharacteristics described above. An increase in the blood pressure ofthe user may indicate, among other things, a higher level of userfrustration or anxiety. An increase in heart rate, or decrease in oxygenlevel in blood, may similarly indicate, among other things, a higherlevel of user frustration or anxiety. A weighted average allows theincorporation of a combination of metrics to measure complexity invarious ways. Instead of simply taking measurements at the beginning andend of a software installation, configuration or usage process, ease ofuse may also be determined or predicted by monitoring various biometriccharacteristics continuously or intermittently throughout software useand then computing an average function over the system.

Based on biometric feedback data, good quantitative measures of softwareease-of-use can be estimated by having a sample set of users try out thesoftware in test settings. Statistical analysis of biometric dataobtained from a group of appropriately-selected testers could be used toproduce a rating of the ease of use of the software.

In addition, peripherals equipped with appropriate biometric sensorscould enable the present invention to be used to identify instances ofsoftware usage difficulties during everyday use of the software, outsideof the context of testing. Computer keyboards and mice can be equippedwith sensors that are capable of monitoring the biometriccharacteristics of a user. A computer mouse, for example, could befitted with sensors to monitor a user's blood pressure, heart rate,temperature of the user, and/or the force exerted each time a mousebutton is clicked. A keyboard could also be fitted with similar sensors,including sensors to monitor the force exerted each time a key ispressed. Measurements taken by such biometric-sensor-equippedperipherals could also be reported back to the software developer inorder to identify instances in which difficulties are encountered inday-to-day use of the software.

Such a system for measuring software ease of use can be used forquantitative measurements in experimental studies conducted for asoftware, as well as to measure the ease-of-use of software by usersduring their production use.

The present invention thus provides a method, a system, and a computerreadable medium providing instructions for using biometrics to determinesoftware ease of use comprising: one or a plurality of sensors tocollect biometric data from a user engaged in using software; a computerto identify changes in said biometric data; a biometrics database, orother source of baseline data, for determining if said changes arerelevant to a determination of software ease of use; and acommunications pathway to generate a signal as output if said changesare relevant to software ease of use. The sensors (one or more innumber) may be integrated into a computer peripheral with which saiduser comes in regular contact while using said software, such as acomputer mouse, keyboard, or other peripheral with which a software useris likely to make frequent contact, such as a computer screen intouch-screen systems or a peripheral attached to the user solely to takebiometric data for purposes of the present invention. (If this is done,the peripheral must be one with which the user comes into regularcontact while using the software, but it does not have to be one withwhich the user remains in constant contact while using the software,though it could be a peripheral with which the user remains in constantcontact.) The biometric data collected by the sensors may or may not becommunicated to a database. The output signal may include, withoutlimitation, data describing the relevance of said changes to softwareease of use. Such data may simply indicate whether the data isconsistent with user ease of use or with user difficulty, and such datamay also include more specific information on the difficultiesapparently being encountered by the user, in which case this signal mayactivate the software's help routine.

The computer implemented method employing biometric measurements, whichis provided according to the present invention, comprises the steps of:using sensors to collect biometric data from at least one user engagedin using software operating on a computer or computer network;monitoring changes in the biometric data occurring while the software isbeing used; and providing an output based on changes in the biometricdata. The output of the computer implemented method may be aquantitative measurement of software ease of use. The quantitativemeasurement of the computer implemented method may be electronicallystored or transmitted to another computer or computer network. Thecomputer implemented method may be applied to multiple users, and thequantitative measurement may be user-independent and/or may be based onbiometric data for each user. The output of the computer implementedmethod may be a context sensitive help message. The output of thecomputer implemented method may be provided based on a user-specificease-of-use measure.

The computer system employing biometic measurements, which is providedaccording to the present invention, comprises: one or more sensors forcollecting biometric data from at least one user engaged in usingsoftware operating on a computer or computer network; and softwareoperating on said computer or computer network which (a) monitorschanges in the biometric data occurring while the software is being usedand (b) provides an output based on changes in the biometric data. Atleast one of the sensors may be associated with a peripheral devicewhich is connected to or communicates with the computer or computernetwork. The peripheral device may be a mouse, tablet, track ball, ortablet. The output of the computer system may be a quantitativemeasurement of software ease of use. The computer system may furthercomprise a storage medium for storing said output. The computer systemmay be applied to a multiple users, and the quantitative measurement maybe user-independent and/or may be based on biometric data for each user.The output of the computer system may be a context sensitive helpmessage displayed on a display. The output of the computer system may bebased on a user-specific ease-of-use measure.

The computer readable medium providing instructions for implementing amethod employing biometric measurements, which is provided according tothe present invention, comprises the steps of: using sensors to collectbiometric data from at least one user engaged in using softwareoperating on a computer or computer network; monitoring changes in thebiometric data occurring while the software is being used; and providingan output based on changes in the biometric data. The output generatedaccording to instructions provided by the computer readable medium maybe a quantitative measurement of software ease of use. The instructionsprovided by the computer readable medium may further compriseinstructions to electronically store or transmit the quantitativemeasurement to another computer or computer network. The instructionsprovided by the computer readable medium may be applied to multipleusers, and the quantitative measurement may be user-independent and/ormay be based on biometric data for each user. The output generatedaccording to instructions provided by the computer readable medium maybe a context sensitive help message. The output generated according toinstructions provided by the computer readable medium may be providedbased on a user-specific ease-of-use measure.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, aspects and advantages will be betterunderstood from the following detailed description of preferredembodiments of the invention with reference to the drawings, in which:

FIG. 1 is a flow-chart representing the steps of an implementation ofthe present invention.

FIG. 2 is a representation of a sample situation in which the presentinvention can be applied to measure the ease of use quantitatively.

FIG. 3 is a representation of a flow chart showing how biometricsmeasurements can be adjusted to account for multi-tasking in a system.

FIG. 4 is a representation of a system for using biometrics to determinesoftware ease of use from users in the field according to the presentinvention.

FIG. 5 is a representation of a computer mouse into which sensors havebeen integrated according to the present invention.

FIG. 6 is a process usable to deliver a type of help-information to auser.

DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT OF THE INVENTION

Referring now to the drawings, and more particularly to FIG. 1, there isshown a basic implementation of the present invention which is used tomeasure the ease of use of a software system. The step 110 is enteredwhen the software being analyzed for ease of use is initiated and isready to receive interaction from the user. In step 120, an initialreading of the biometric data from a user engaged in using the softwareis taken. This reading can be taken when the user starts the softwaresystem on his/her computer. Some software systems are already running asbackground processes in a computer system (e.g., as daemon processes inUNIX operating systems). In the context of those systems, this readingcan be taken when the user makes the first interaction with the softwaresystem. In step 130, more biometric data is collected and the changesfrom the original biometric data is determined. This would indicateconditions such as an increase in blood pressure, or a decrease in bodytemperature. In step 140, the biometric changes recorded are combinedinto a quantitative metric reflecting the software complexity. Adetermination is made in step 150 whether the software is still beingused by the user. If so, the algorithm repeats back to step 130 in whichmore biometric measurements are taken and the quantitative measurementof the software complexity is updated. If the software is not activelyused, the process terminates in step 170.

There are several biometric measurements that can be taken and combinedas part of this process. FIG. 2 shows an illustrative example thatprovides a means by which the ease of use of a software component can bedetermined. Consider the case of a software application which is used byemployees of a corporation to order supplies for their business needs,e.g. office supplies, computer parts and peripherals, and other materialthat needs to be procured. An employee running this software is usingcomputer peripherals that are able to monitor and record his biometricdata. Although many different types of biometric data can be recorded,for illustration purposes we will assume that his heart-rate,blood-pressure and body temperature are the three metrics beingrecorded.

FIG. 2 shows the snap-shot of the instances at which the measurement ofthe biometric data is made. The biometric data can be measured by thecomputer user every time a mouse-click or keyboard entry is made on theuser-interface provided by the software. The user goes through the stepsof typing the name of an article being procured (210) and searching forit (220), selecting the article that is to be procured from the resultsof the search (230), selecting a vendor for the article (240),completing the accounting information for the article (250), and thencreating the procurement order (260). Table 211 shows the biometricinformation collected when the program is initially launched. Table 221shows the biometric information collected when step 220 is completed,table 231 shows the biometric information collected when step 230 iscompleted, table 241 shows the biometric information collected when step240 is completed, table 251 shows the biometric information collectedwhen step 250 is completed, and table 261 shows the biometricinformation collected when step 260 is completed. In each table, theblood pressure (BP) is shown as systolic/diastolic measures, thetemperature (Temp) in degrees Fahrenheit, and the heart rate (HR) inpulses per second.

On comparing the biometric data obtained in this manner, one candetermine that the blood pressure of the user has slightly increased,and his heart-rate is also slightly increased, while the temperatureremains relatively constant. A weighted average of the relative changesin the three metrics serves as a quantitative measure of the softwarecomplexity of the program being used. One simple manner to combine theease of use would be to look at the relative change in the biometricdata at the beginning and the end of the phase using the application.According to that metric, the systolic blood presume has increased by3.8%, the diastolic blood pressure has increased by 6.6%, the heart ratehas increased by 7.7%, and the temperature has increased by 0.003%. Allof the changes are in the negative direction (what one would expect whenthe user of the software is vexed). These percentage rates of changescan be averaged to assign an ease of use index of −4.525 for thisparticular user. Another user may have different indexes that will beobtained from observing their reaction to the program. Averaging acrossmultiple users will provide the average ease of use index for thisapplication.

The metric provided in the above example is rather simplistic. In actualuse, a metric that incorporates the fluctuations in the differentreadings is likely to be a much better indicator of the ease of use thansimply measuring the initial and final biometric information. An exampleof such a measurement would be to take the relative change over time ofthe various indexes, and then use the average rate of change in eachmetric as the information to feed in determining software complexity.

Assuming that the user spends the same amount of time between each ofthe various steps shown in FIG. 2, the average rate of changes in eachof the biometric measures being taken are as follows:

Change Change Change Change Change Average Metric 210-220 220-230230-240 240-250 250-260 Change Systolic BP 3.84% −3.7% 3.84% 0%   0%0.7% Diastolic BP 3.33% 3.22%   0% −3.1%   3.22% 1.3% Heart Rate  2.5%−1.25%   3.8% 2.4%     0% 1.5% Temperature   0% 0.05% 0.00% 0% 0.03%  0%

When computing the ease of use index, the weights assigned to each ofthe individual metrics need not be equal. Let us say that the weightsassigned to systolic blood pressure, diastolic blood pressure, heartrate and temperature is in the ratio of 2:2:1:1. In that case, the easeof use index of the software using this method of computation would be−0.7. In general the higher the ease of use index, the moreuser-friendly the software is.

Other formulas than the ones shown above can be used to compute the easeof use index.

The ease of use index as computed above would be different for each ofthe users that invoke the applications. The information obtained fromdifferent users needs to be complied into a single quantitative measurefor ease of use index for the software, which can then be used as auser-independent index for its ease-of-use.

One way to obtain a user-independent metric is by conducting studies andtests for users when they invoke a given application. Each user involvedin the study would be monitored to determine a user-specific ease-of-useindex for the software. Then the user-independent indices can becombined to form the user-independent ease-of-use index. An average ofthe user-specific indices can be used as the user-independent index, orother aggregation metrics, e.g., the spread (minimum and maximum) can beused as the user-independent ease-of-use index, or a percentile spreadthat eliminates outliers can be used.

The second approach would be to determine the ease-of-use of softwarewhen it is being used in deployment by real end-users, as opposed to atest environment or a field-study. The proposed invention provides a wayto obtain the biometric information from the end-users of an applicationsoftware so as to determine a user-independent estimation of softwareease-of-use.

One of the problems in determining the ease of use of a softwareapplication in real use is the problem that people do not necessarilyspend all the time continuously working on the same application. As anexample, let us consider the case of the procurement applicationdiscussed in FIG. 2. In a real enterprise use, the procurementapplication may be deployed using as an application on the desktop ofemployees. An employee may have several applications deployed on thedesktop, and can switch from one application use to another at differenttimes. Thus, an employee may look up an item in the procurementapplication, then look for some specifics for that article on the web,and then return to the procurement application. Switching amongdifferent applications can impact the biometric data for the employees,and the interference from different applications needs to be taken intoaccount when determining the ease of use for any given application.

FIG. 3 describes the process by which the interference from differentapplications can be taken into account. The process is started in step310 when a user logs on to the computer to use it for any purpose. Thecomputer is connected to different peripherals that can monitor andrecord biometric information. The computer keeps on recording thebiometric information 320 at periodic intervals, at user-initiatedevents such as mouse-clicks and keyboard input. At each of the userinitiated event, the computer keeps track of the application to whichthat input is directed. The application that is the focus of userinteraction is tracked in step 330. When the measurement is time-driveninstead of user-initiated, the window in which the user input is focusedon is taken as the application on which focus is directed. In step 340,the biometric information is recorded separately for the differentapplications to which the user is switching to. Some of the usergenerated events, e.g. mouse clicks or application launches, cause focusto switch on to different applications. Users biometric information iscollected both when an application goes out of focus and when a newapplication is brought into focus.

Every time a new biometric data is recorded, the process checks to makesure if a recording event has occurred in step 350. A recording eventmay include termination of an application, or when an application hasnot been used for a pre-determined amount of time implying it has beenimplicitly terminated. If a recording event has occurred for anyapplication, in step 360 the process computes a complexity metric forthe application by looking only at those biometric data points that havebeen collected when the application was in the focus, moved into thefocus, or moved away from the focus. After this reporting, the processcontinues to collect biometric information from the user.

Having determined only the biometric data points that are relevant foran application, software ease of use in the field is determined by meansof a set up shown in FIG. 4. A user 410 is shown using a computer 420 towhich peripherals capable of taking biometric measurements are attached.An example of such a peripheral is a mouse 430 which integrates withinitself sensors that can collect biometric readings such as bloodpressure and heart-rate. Another example of such as a peripheral is akeyboard 440 which can measure the force with which users are typing onthe keyboard, and use increase in that force as a measure of userfrustration. The computer includes software 450 which is used forcreating the application specific data-set described by the process ofFIG. 3. The software 450 reports the biometric data metrics for anapplication of the user via a computer network 460 to a server 470. TheInternet is an example of the computer network 460. The server 470receives the information from other users of the application, e.g., auser 480 which is working on a separate computer 490. The server 470combines the biometric information from all of the users to obtain auser-independent ease-of-use index.

The structure of software 450 which can be used for collecting ease ofuse information from the field is provided in FIG. 5. The softwareconsists of means to collect and record biometric data from peripherals510; a means for mapping the current interface to an application 520; ameans for mapping an application to a server 540; a database to storethe biometric information for each application 530; a means to calculatethe software ease of use for any application 550; and a means tocommunicate over the network 560. The means to collect and recordbiometric data from peripherals interacts with devices like keyboard andmouse with enhanced sensors to obtain the current biometric readings fora user. The component 520 is responsible for mapping the current windowon which a user is focused, the current console to which typing; or theinput that he is using to an application. This component can performthis mapping by knowing which process owns the window/interface that iscurrently being focused on, and by determining the application that ownsthat process in the operating system. The component 540 determines theserver that needs to obtain the information about the application easeof use over the Internet, or another such network. The component 530stores the biometrics information for processing into the ease-of-useindex for the current user. The database can be uploaded to a serverover the network, if required. The component 550 is responsible forexecuting the algorithms described in FIG. 1 and FIG. 3 of theapplication. Component 550 can be implemented as a set of libraries,each one customized for a specific application, or as a generic softwaremodule which can be reused for multiple applications by defining someconfiguration parameters. The reporting of information to the server onthe network happens via the network communication module 560.

The system used for collecting ease of use information can be used forpurposes other than simply reporting software ease-of-use metrics. Theinformation can be used to identify when users are having problemsdealing with a specific software component, and a help menu can beinitiated when the user is perceived to be having problems in using thesoftware. A context sensitive help information can be popped up to theuser to provide helpful information about the software that he/she isencountering difficulty with.

A process that can be used to deliver this type of help-information isshown in FIG. 6. The process is entered in step 610 when a user logs-in,and it continuously monitors the biometric characteristics of the useras determined to be relevant for an application according to the flowchart shown in FIG. 3. The system continuously keeps on computing theease-of-use index for the application in step 620. When the ease-of-useindex falls below a predefined threshold in step 630, the system promptsthe user if he would like help with the application in step 640.Depending on the relative priority of the user, the user may beconnected to the help-desk that can guide the user through theapplication. Alternatively, context-sensitive help menus can be shown inthe screen of the user to provide assistance in the task that he/she isinvolved in. Otherwise, the system checks that the application is stillbeing used in step 650 and if so continues to check the ease of useindex in step 620. If the application is not being used, the processterminates in step 660.

The information collected about biometric data of users can be analyzedto create other applications. One such analysis would be to computesoftware ease-of-use indices for different steps required within anapplication, as opposed to computer the ease-of-use for the overallapplication. The portion of the software that is determined to bedifficult to use can then be modified to improve its usability.

Having thus described our invention, what we claim as new and desire tosecure by Letters Patent is as follows:
 1. A computer implemented methodfor quantitative determination of software ease of use, comprising thesteps of: using sensors to collect biometric data from each of aplurality of users engaged in using a software application operating ona computer or computer network; monitoring and recording changes in thebiometric data which occur while the software application is being usedby each of the plurality of users; combining recorded changes in thebiometric data for each user into quantitative metrics; averagingquantitative metrics across the plurality of users; compiling theaveraged quantitative metrics into a single quantitative measure for anease of use index for the software application; and providing an outputas a user-independent index for ease-of-use of the software application.2. The computer implemented method of claim 1 wherein more than onesoftware application may be running on a computer used by anyone of theplurality of users, further comprising the steps of: determining aspecific software application for which an ease-of-use index is to bedetermined; and for the specific software application, creatingapplication specific biometric data used in determining theuser-independent index for ease-of use of the software application. 3.The computer implemented method of claim 1, wherein saiduser-independent index for ease-of-use of the software application iselectronically stored or transmitted to another computer or computernetwork.
 4. The computer implemented method of claim 1, furthercomprising the steps of: establishing a threshold for the ease-of-useindex for a software application; determining if the threshold has beenexceeded by an individual user of the software application; and if thethreshold is exceeded by the individual user, displaying a contextsensitive help message.
 5. The computer implemented method of claim 4wherein said context sensitive help message is provided based on auser-specific ease-of-use measure.
 6. A computer system for quantitativedetermination of software ease of use, comprising: sensors forcollecting biometric data from each of a plurality of users engaged inusing a software application operating on a computer or computernetwork; and software operating on said computer or computer networkwhich a) monitors and records changes in the biometric data which occurwhile the software application is being used by each of the plurality ofusers; b) combines recorded changes in the biometric data for each userinto quantitative metrics; c) averages quantitative metrics across theplurality of users; d) compiles the averaged quantitative metrics into asingle quantitative measure for an ease of use index for the softwareapplication; and e) provides an output as a user-independent index forease-of-use of the software application.
 7. The computer system of claim6 wherein at least one of said sensors is associated with a peripheraldevice which is connected to or communicates with said computer orcomputer network.
 8. The computer system of claim 7 wherein saidperipheral device is a mouse, tablet, track ball, or tablet.
 9. Thecomputer system of claim 6 wherein said user-independent index forease-of-use of the software application is electronically stored ortransmitted to another computer or computer network said output is aquantitative measurement of software ease of use.
 10. The computersystem of claim 9 further comprising a storage medium for storing saiduser-independent index for ease-of-use of the software application. 11.The computer system of claim 6, wherein for a specific softwareapplication a threshold is established for the ease-of-use index for thespecific software application, said software operating on said computeror computer network further f) determines if the threshold has beenexceeded by an individual user of the software application; and g) ifthe threshold is exceeded by the individual user, displaying a contextsensitive help message displayed on a display.
 12. The computer systemof claim 11 wherein said context sensitive help message is providedbased on a user-specific ease-of-use measure.
 13. A computer readablenon-transitory medium providing instructions for implementing a methodfor quantitative determination of software ease of use, comprising thesteps of: using sensors to collect biometric data from each of aplurality of users engaged in using a software application operating ona computer or computer network; monitoring and recording changes in thebiometric data which occur while the software application is being usedby each of the plurality of users; combining recorded changes in thebiometric data for each user into quantitative metrics; averagingquantitative metrics across the plurality of users; compiling theaveraged quantitative metrics into a single quantitative measure for anease of use index for the software application; and providing an outputas a user-independent index for east-of-use of the software application.14. The computer readable non-transitory medium of claim 13 wherein morethan one software application may be running on a computer used byanyone of the plurality of users, further comprising the steps of:determining a specific software application for which an ease-of-useindex is to be determined; and for the specific software application,creating application specific biometric data used in determining theuser-independent index for ease-of use of the software application. 15.The computer readable non-transitory medium of claim 13, furthercomprising instructions to electronically store or transmit saiduser-independent index for ease-of-use of the software application toanother computer or computer network.
 16. The computer readablenon-transitory medium of claim 13, further comprising instructions forimplementing the steps of: establishing a threshold for the ease-of-useindex for a software application; determining if the threshold has beenexceeded by an individual user of the software application; and if thethreshold is exceeded by the individual user, displaying a contextsensitive help message.
 17. The computer readable non-transitory mediumof claim 16 wherein said output is provided based on a user-specificease-of-use measure.